a review on optimization of system of systems 1 ...

9th International Automotive Technologies Congress OTEKON 2018 7-8 May 2018, BURSA

A REVIEW ON OPTIMIZATION OF SYSTEM OF SYSTEMS

Merve Akkaya, Mostafa Ranjbar

Ankara Yildirim Beyazit University, Department of Mechanical Engineering, Ankara, Turkey Corresponding Author: [email protected]

ABSTRACT System of systems is a combination of goal-oriented set of systems to produce a new system which offers more functionality and performance. Also, optimization of System of Systems improves the performance of such new complex system. It brings many advantages in industrial applications like automotive engineering. This paper presents a study on optimization of system of systems (SoS). It applications in automotive systems and transportation systems are reviewed. This can provide a clear overview on the topic and gives some guidelines for future investigation and application in ongoing automotive engineering industries. Keywords: Minimum three, System of systems, Optimization, Application, Design, Automotive, Review

1. INTRODUCTION Nowadays, computers help us to get better optimization performance even for very complex systems. As a result, it can be possible to get better optimization results when subsystems have been already optimized for increasing individual quality. SoS term is arisen in which the individual systems are embedded. In fact, it consists of a set of systems which are independent from each other. When they are combined into larger systems, they become exclusive properties [1]. With these systems, very large systems may have developed by forming frameworks to integrate constituent systems. The multi objects system which consists of many individual components, can cause complicated analyses. It is explicit that a special numerical analyse is required to analysing SoS at the global level, because optimization of each individual components may not give optimality of their collaboration. System of systems is almost new research area. While many researchers and scientists used it, there is almost no certain definition of it. But, it is obviously clear that SoS is comprised of many small systems or subsystems which come together for gain new properties [2]. SoS describes integration of many small components to obtain global needs of multi-systems. For example, car and road are system while product range, integrated traffic system is SoS. Aeroplane is a system while airport or air traffic control system is SoS. Train is a system while station, signaling, rail network is SoS. Building is a system while shopping mall is a SoS. Also, there are some examples about biological, sociological, environmental, organisational and political SoS. System of systems engineers (SoSE) should encourage multiple purposes and visions of systems. They should optimize the system of systems in a useful way. There are some differences between system engineering and System of Systems engineers (SoSE).

2. SYSTEM OF SYSTEMS (SOS) APPLICATION The system of system is used in many science and technology fields such as military, security, aerospace, manufacturing, transport, environment systems, and disaster governing. In the following, we will discuss more about them. In Hayden and Jeffries [4] presented a study about flexible Joint Polar Satellite System (JPSS) was objected to design forecast of weather conditions. JPSS improves weather forecast, ensures safe shipping travel and reduces its cost, ensure safer military operations and helps energy generation. In Nanayakkara and Jamshidi [5] explained for Future Combat Missions (FCM) for defence national security. It composes of 18 manned or unmanned systems connected with

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information network. It has high range ability about defence, stability, manoeuvrability, survivability and reliability. SoS is caused improving performance in these cases. Samuel [6] presented the Target Evaluation and Correlation Method" (TECM) as an assessment approach to Global Earth Observation System of Systems (GEOSS). A new method which was about evaluation and correlation levels of targets was explained. Target Evaluation and Correlation Method was used to specify the Target Correlation Level (TCL). The proposed TECM process and applications were presented in the various parts of GEOSS Implementation Plan. Klein and Vliet [7] studied the systematic review of system-of-systems in architecture research. They showed results of a systematic review from SoS architecture perspective. The purpose of this research was to analyse the scope of system of system for architecting reports. Davendralingam and DeLaurentis [8] presented a work on robust optimization framework to architecting system of systems. Optimization of architecting system of systems in resilient was presented. Interdependent systems were used with modelling fulfil overarching capability objectives. The newest robust optimization methods were applied with Mixed-Integer Program (MIP) for improving framework. Embedded systems provide improving performance of system; perform completely new functions of system. When embedded system is used, system is changed completely. Embedded systems are using many applications. There are many explanations about automotive electronics applications and technologies. Automotive system safety analysis and cost efficiency were explained with Larses thesis [9]. It [9] was included architecting and modelling automotive embedded systems. In Shin and Lim [10] studied about Unified Modelling Language (UML) model-based automatic test case generation for automotive embedded software testing through model-based approach. They developed a method for automatically generating software and hardware test cases. With this method, hardware and software test case generation required sources could be decreased. Also, Samuel mentioned a method for producing UML state diagrams using in automotive systems. Gulia and Chillar [11] produces some test cases with using UML diagrams. Florin and Norbert [12] also investigated optimization of mergence test cases for automotive systems. DeLaurentis [13] performed a study of understanding transportation as a system of systems design problem. System of systems was introduced in aerospace design implications. Future transportation systems were described, as well.

3. OPTIMIZATION BASED DESIGN Optimization is a mathematical discipline which intends to improve ability of the systems. It can be using in many fields such as architecture, nutrition, electrical circuits, economics, transportation, military, defence and [14]. Strong engineering designs based on optimization methods. Using optimization methods, inputs (analysis variables) of system should be known for making calculations. Analysis variables are composing of design variables and other quantities such as material properties. Analysing outputs are called as analysis functions such as stress, deflection, COP value [15]. Optimization is a finding an alternative way with maximization desired factors and minimizing undesired factors. General purpose is finding most cost-effective way or obtaining highest performance way with system constraints or boundaries. There are various optimization methods available. However, the most efficient and robust solution method should be selected. For each specific case selecting most appropriate optimization methods, some optimization methods are explained below. Linear programming method can be used in wide-range of optimization problems. Many engineering, and economics problems can be solved with this method. Manufacturing, transportation and many other design problems are solved using this method. Linear objective function is minimized or maximized with respect to unknown variables and inequalities [16]. Disadvantage of this methods are lack of risk assessment and using only linear objective functions [14]. Non-Linear programming method is for solving of optimization problems with equality and inequality systems. Nonlinear objective function is minimized or maximized in unknown variables and inequalities [17]. Many algorithms may not find the global minimum. This method applicability is limited. In fact, this method is suitable for specific kinds of problems [14]. Gradient methods are using minimizing convex differentiable equation. Non-differential equations are not solved by this method. It is generally not fast. Objective function shouldn't be noisy for obtaining accurate results [14].

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Gradient free methods include multiple objectives. It is using with non-differentiable equations and/or constraints. It is effective for finding local minimum nonlinearity constrained problems [18]. Evolutionary Algorithms methods are created from biological evolutionary such as mutation, recombination of genes. Finding solutions may not be cheap. Parameter adjustment is accomplished by trial-error method [14]. Probabilistic approach method is efficient in computational solutions. Also, it is less efficient than non-probabilistic ones [19]. Fuzzy Logic method writing task about the formulation may be challenging. It has more than one way for compound evidence. Problems can solve with long inference chains. It is not efficient for complex parts [20]. Swarm algorithms method inspired from natural swarm systems such as ant colony. It has low cost while it has fast solutions. It has robust solutions above complex problems. It can be practiced in a wide variety area with many problems. It hasn't central control which makes causing this system inefficient [21]. Multi objective optimization method is using many mixed optimization problems (min-max). It is recommended that changing all objectives to same type. Optimal solutions are termed as Pareto solutions. There may be multiple minimum solutions with this method [18]. There are many researches about optimization of energy systems. Hennet and Samarakou [22] had a study about optimization of combined solar and wind power plant. Also, optimal capacity of a battery storage system was investigated. Lozano, Valero and Serra [23] were presented local optimization of energy systems. This paper demonstrated about exegetic and marginal costs theory from every component of system. It was found that global optimization methods were proposed method for these type calculations. Peippo and Vartiainen [24] studied about optimization procedure in order to defining optimal design buildings in early design stage. Shi et al. [25] was presented a study about PV, wind hybrid power system thermo economic analysis and created robust optimal system. Rezvan et al. [26] was studied about a robust optimization method to defining optimal energy generating technologies. Qasaimeh [27] was investigated optimization of the angle of inclination for solar energy for every month and seasons. Sauchell et al [28] presented study about integrating a device into the PV system leads to optimizing solar energy production. Good et al [29] presented optimization of solar energy potential for buildings in urban areas. They tried to find optimal solutions using solar energy in buildings of urban places. According to these examinations, different solar technologies were tried and found that solar thermal systems were substantially bigger annual yield output than PV systems. Wang et al [30] presented multi objective robust optimization of energy systems for a sustainable district in Stockholm study. They were investigated multiobjective robust optimization approach for minimizing greenhouse gases and life cycle cost viability in energy systems. There are many methods and papers about reducing torsional vibrations for automotive systems with addition flywheels of the system [31]. These flywheels work in tune with vibration dampers [32]. In Alsuwaıyan and Shaw [33] presented a study about performance and dynamic stability of general-path centrifugal pendulum vibration absorbers of automotive system. Centrifugal pendulum vibration absorbers were using many machines to decreasing torsion vibrations. With this study, a few identical centrifugal pendulum vibration absorbers performance and dynamical stabilities were researched. According to research results, performances of systems were restricted as two separate types and some advices were given for selection of parts [34] a new method was applied for optimization and development of torsion vibration dampers. Aim of this method was join the simulations into the initial stages of development. In Zink and Hausner [35] presented the centrifugal pendulum-type absorber. Decreasing fuel consumption with producing high torques at low speeds is important for obtaining driving pleasure. Centrifugal pendulum-type absorber was developed by LuK [35] (In this study, this type absorber was developed using as an isolation material in drive systems. In Mall et al [37] presented the simulation based optimization of torsion vibration dampers in automotive power trains. Isolation materials used in automated design was researched and many drive train and dumper types were shown to make dynamic analysis of design. Numerical optimization operation was applied to find the most appropriate geometric parameters. Augmented Lagrangian Particle Swarm optimization method was applied successfully. Suspension systems are using automotive system widely. Nakai et al [38] studied about the development suspension system with gimbals, actuators and a gain-scheduling controller for a flywheel battery on electrical or hybrid electrical vehicles. Els et al. [39] found spring and damper characteristics were needed for driving comfort. In Gysen et al [40] presented a study about design aspects of an active electromagnetic suspension system for automotive applications. An active electromagnetic suspension system was designed with tubular permanent-magnet actuator to provide extra stability and safety. Passive and new designed system was compared. Also, many researchers optimized suspension systems using genetic algorithm method [41]. MATLAB simulation, analysis tools and FEM (Finite Element Method) was used many researches to optimize suspension systems [42]. In Abbas et al [43]. presented a study about optimal seat and suspension design for a half-car with driver model using genetic algorithm to reducing vibration of human body during driving.

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Genetic algorithm was applied for finding optimal parameters of suspension design. With this type of algorithm, (with the determined parameters interval) closely optimal solutions were found. Genetic algorithm solutions were compared with passive suspensions. In Mitra et al [44] presented a study about design of experiments for optimization of automotive suspension system using quarter car test rig. The objective of this research was obtaining ideal suspension and steering geometry parameters. Different combination of steering geometry parameters with suspension was investigated. Then, optimum combination was found, tested and obtained results with compared other results. In Xue et al [45] presented a study about optimization of spring stiffness in automotive and rail active suspension systems. In this research, spring stiffness which is important effect on suspension systems was improved with using a new multi objective optimization method. Ride comfort, safety, reliability stiffness effect on actuator and many considers are taken into for assessment. Then, it was deduced that used new optimization method was effective and it can be used widely in automotive and rail active systems. In recent years there are many researches relation between gear profile and kinematic flow pulsations. Bonacini [46] is one of the authors work about this relation. He also proofed theoretical flow of an EGP (External gear pump) based on involute profile of the gears. Same information was also mentioned by Ivantysyn [47]. In Vacca and Guidetti [48] presented a study about optimization of relevant design parameters of external gear pumps for automobiles. This paper was identified external gear pumps numerical analysis and procedure. Also, this paper focused on optimization pump and bearing blocks and optimized design prototype was tested. Measured results and experimental results were compared. Mucchi et al [49] studied about dynamical behaviour of gear external pumps and experimental and simulation results were compared. Fiebig and Korzyb [50] studied about vibration and dynamic loads in external gear pumps with using simulation model. In Zhao and Vacca A. [51] presented a study about formulation and optimization of involute spur gear in external gear pump for automotive. The purpose of this paper was improving design of asymmetric tooth geometry involute gear and formulation of flow rate with asymmetric and symmetric gear pump. Multi-objective numerical optimization algorithm was used as an optimization method. It was observed that researched gears how higher performance on standard gears. Also, it was shown how parameters impress tooth profile asymmetry. Lee and Yoo [52] had a study about improving simulation program for automotive air conditioning system. With using simulation program, operation parameters effect on the system performance was investigated. In Jabardo et al [53] had a study about modelling and experimental evaluation of an automotive air conditioning system with a variable capacity compressor. Air conditioning system was using automotive sector in order to supply comfort and high efficiency. Computer simulation model was improved for automotive air conditioning system. Both simulated and experimental results were compared. According to results, simulation results were shown almost actual performance with small deviations. Skiepko [54] present a condenser model and made calculations with this model, then it was shown that flow regime and steam quality values affect heat transfer and efficiency. In Khayyam H. et al [55] had a study about reducing energy consumption of vehicle with using air conditioning system. Energy management system (EGM) and without EGM simulation was researched. With this study, EGM comfort temperature was obtained in cabin in automotive with reducing energy consumption. EGM and without EGM simulation results were compared. Tian et al 2014 [56] were modelled a parallel flow condenser and optimized this model with Lavenberg-Marquardt algorithm method. In Shojaeefard et al [57] had a study on multi-objective optimization of an automotive louvered fin-flat tube condenser for enhancing HVAC system cooling performance. The objective of this research was creating higher coefficient of performance (COP) automotive refrigeration and cabin design. Multi objective optimization method was used in HVAC system design of this system. According to this study, optimization designed of cooling system COP value and cooling capacity value were increased when compared non-optimized model. In Zhang [58] presented a study about design and testing of an automobile waste heat adsorption cooling system. Absorption systems were using automotive sector for reducing greenhouse gases. Bruno et al [59] study purpose was showing effect of post-combustion degree on the integrated system performance on the integration of micro gas turbines (MGT) and absorption chillers. Main advantage of this study was COP of chillers was higher and this reason were explained in the paper Critoph et al [60]. To increasing system performance, some control systems were designed. Also, adsorption cooling system was designed and tested by experimentally. According to results, this system can be used for waste heat adsorption cooling system. COP values were also so supportive according to this paper. Javani et al [61] was investigated compare of two refrigeration cycle with available waste heat as a used in hybrid and electric vehicles to cool the cabinet of automotive. In Pang et al [62] presented a review about liquid absorption and solid adsorption system for household, industrial and automobile applications. This paper involves innovative ways of adsorption system which were liquid absorption and solid absorption systems. It was observed that absorption and adsorption systems were decreasing

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fossil fuel usage, clean energy supplier, cheap and incrementally increasing in the future. In Verde et al [63] presented a study where dynamic performance of all system was tested and cabin temperature was estimated with wasted heat in Fiat Grande Punto vehicle. Unique design types were investigated for increasing system efficiency. It was seen that supplied engine waste heat was enough for cooling in the cabinet. In a series of publications by Ranjbar et al. from 2007 to 2017, the concept of multidisciplinary engineering design optimization of various automotive structures was investigated and reported. They showed the effect of optimization in the quality of results. Furthermore, they presented very innovative techniques for improving the optimization results for real industrial automotive applications by using novel optimization methods [65-93].

4. CONCLUSION The brief review of the optimization system of systems (SoS) was explained, SoS main structure and general definition of it were introduced. System of systems engineering (SoSE) duties were clarified briefly and application of SoS were mentioned with this study. Various applications of the SoS concept were explained based on mechanical engineering area. Examples of optimization of SoS in automotive engineering field like suspension system design and cooling system design were presented. A brief survey was done on application optimization on SoS. This showed that this field will be emerging in the next decade, especially by development of self-drive cars. More advance SoS will be used in electrical cars to protect the environment and provide better service to the community.

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[69] Ranjbar, M., Hardtke, H-J., Fritze, D., Marburg, St. (2010) “Finding the Best Design within Limited Time: A Comparative Case Study on Methods for Optimization in Structural Acoustics,” Journal of Computational Acoustics, 18, 2, pp. 149-164. [70] Ranjbar, M., Marburg, St., Hardtke, H-J. (2012) “A New Hybrid Design of Experiments Approach for Optimization in Structural Acoustics Applications,” Applied Mechanics and Materials, 110-116, pp. 5015-5020. [71] Ranjbar, M., Tadayon, A. (2017) “Vibration Analysis of Multi Degree of Freedom Self-Excited Systems”, Journal of Robotic and Mechatronic Systems, 2, 1, pp. 1-8. [72] Ranjbar, M., Nahid, M., Renawi, A., Sadeqi, Z. (2017) “Development of an Educational Noise Reduction Measurement Test Bench”, Journal of Robotic and Mechatronic Systems, 2, 1, pp. 27-32. [73] Ranjbar, M., Alinaghi, M. (2016) “Effect of Liner Layer Properties on Noise Transmission Loss in Absorptive Mufflers”, Mathematical Modelling and Applications, 1, 2, pp. 46-54. [74] Ranjbar, M., Gharooni Saffar, M. (2016) “A Sensitivity Analysis on Application of Artificial Neural Networks in Structural Acoustics”, Journal of Robotic and Mechatronic Systems, 1, 2, pp. 23-26. [75] Ranjbar, M., Kemani, M. (2016) “A Comparative Study on Design Optimization of Mufflers by Genetic Algorithm and Random Search Method”, Journal of Robotic and Mechatronic Systems, 1, 2, pp. 7-12. [76] Ranjbar, M., Marburg, St. (2013) “Fast Vibroacoustic optimization of mechanical structures using artificial neural networks”, International Journal of Mechanical Engineering and Applications, 1, 3, pp. 64-68. [77] Ranjbar, M., Marburg, St. (2013) “Vibroacoustic Optimization of Mechanical Structures: A Controlled Random Search Approach,” Advanced Material Research, 622-623, pp. 158-161.

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[78] Ranjbar, M., Marburg, St. (2012) “Vibroacoustical Optimization of Mechanical Structures Using Geometry Modification Concept and Genetic Algorithm Method”, Journal of Mechanical Engineering, Tarbiat Modares University, 12, 2, pp. 134-143. [79] Ranjbar, M. (2011) “A Comparative Study on Optimization in Structural Acoustics”, Ph.D. Thesis, Technische Universität Dresden, Germany. [80] Ranjbar, M. (2007) “Development of Hybrid Robust Optimization Strategies for Structural-Acoustic Applications,” In the annual report of the Pan-European Research Infrastructure on High Performance Computing (HPC-Europa), University of Bologna, Italy. [81] Ranjbar, M., Khadem, S. E. (2001) “Development of vibration analysis using Gabor transformation for machinery fault diagnosis “, Journal of Amirkabir University, 12, 48, in Persian. [82] Ranjbar, M., Keskin, O., Demirtaş, S., Karakoca, Y. E., Arslan, H. (2017) “Designing and Manufacturing of a Modal Analysis Test Bench – Part one: Harmonic Shaker Development”, International Symposium on Multidisciplinary Studies and Innovative Technologies Gaziosmanpaşa University Tokat / Turkey. [83] Ranjbar, M., Dalkılıç, B., Çalık, E., Arslan, M. C., Arslan, H. (2017) “On Muffler Design for Transmitted Noise Reduction”, International Symposium on Multidisciplinary Studies and Innovative Technologies Gaziosmanpaşa University Tokat / Turkey. [84] Mazloomi, S., Ranjbar, M., Sarpa, F., Ozada, N. (2017) “Vibroacoustic Optimization of 2-dimensional gradient auxetics sandwich panels”, Medyna 2017: 2nd Euro-Mediterranean Conference on Structural Dynamics and Vibroacoustics, Sevilla, Spain. [85] Ranjbar, M., Orhan, S. (2017) “Self-Excited Vibration of the Three-Degrees of Freedom System”, the 25th Annual International Conference on Mechanical Engineering (ISME 2017), Tehran, Iran. [86] Ranjbar, M., Kermani, M. (2014) “Muffler Design by Noise Transmission Loss Maximization on Narrow Band Frequency Range”, the 7th Automotive Technologies Congress (OTEKON 2014), 26-27 May 2014, Bursa, Turkey. [87] Ranjbar, M., Kermani, M. (2013) “On Maximization of Noise Transmission Loss in Mufflers by Geometry Modification Concept”, ASME District F - 2013 Early Career Technical Conference, 2-3 November 2013, University of Alabama, Birmingham, Alabama, USA. [88] Ranjbar, M., Marburg, St., Hardtke, H.-J. (2011) “Development of a Hybrid Neural Networks Algorithm for Structural-Acoustics Optimization Applications”, In Proceedings of the First International Conference of Acoustics and Vibration, 21-22 December 2011, Tehran, Iran. [89] Ranjbar, M., Marburg, St., Hardtke, H.-J. (2011) “Schnelle Optimierung in der Struktur Akustik”, the 37-annual meeting for Acoustics, 21-24 March 2011 Düsseldorf, Germany. [90] Ranjbar, M., Marburg, St., Hardtke, H.-J. (2007) “Ein Vergleich von Optimierungsverfahren fuer Anwendungen in der Strukturakustik,” Proceedings of the 33-annual meeting for Acoustics, 19-22 March 2007, Stuttgart, Germany. [91] Ranjbar, M., Marburg, St., Hardtke, H.-J. (2006) “Study of Optimization Methods for Structural-Acoustic Applications,” Proceedings of 77th Annual Meeting of the Gesellschaft für Angewandte Mathematik und Mechanik e.V., 27-31 March 2006, Technische Universität Berlin, Germany. [92] M. Ranjbar, M. Mirsalim, “Feasibility Study Phase for the Implementation of Hybrid Electric Vehicles in IRAN “, Eight Grove Fuel Cell Symposium, Poster Presentation, 24-26 September 2003, London, UK. [93] M. Ranjbar, M. Mirsalim, “A Feasibility Study Phase on the Hybrid Electric Vehicles For Iran “, The First International Conference on HEV’s, Iran Science and Technology University, Tehran, Iran, in Persian (April 2001).